Review
Education & Educational Research
Elham Mousavinasab, Nahid Zarifsanaiey, Sharareh R. Niakan Kalhori, Mahnaz Rakhshan, Leila Keikha, Marjan Ghazi Saeedi
Summary: This study focused on the variant characteristics of Intelligent Tutoring systems (ITSs) developed in different educational fields, mainly utilizing artificial intelligent techniques such as action-condition rule-based reasoning, data mining, and Bayesian network. These techniques enable personalized guidance, assessment of learners, and adaptive instruction in ITSs.
INTERACTIVE LEARNING ENVIRONMENTS
(2021)
Article
Computer Science, Artificial Intelligence
Doaa Mohamed Elbourhamy, Ali Hassan Najmi, Abdellah Ibrahim Mohammed Elfeky
Summary: Modern approaches in education technology, such as electronic books, infographics, and mobile applications, are being used to improve education quality and learning levels. Educational data mining is a popular method for predicting student performance and monitoring progress. A model was developed to inform students about their performance in a computer networks course, and the effectiveness of infographics for teaching was proven.
PEERJ COMPUTER SCIENCE
(2023)
Article
Education & Educational Research
Yue Wang, Tessa H. S. Eysink, Zhili Qu, Zhijiao Yang, Huaming Shan, Nan Zhang, Hai Zhang, Yining Wang
Summary: This research investigated the impacts of using IRS in an ILE on students' academic performance, cognitive load, and satisfaction with the lesson. The findings showed that students in the experimental group had higher academic performance, lower cognitive load, and higher satisfaction with the lesson compared to the control group.
JOURNAL OF EDUCATIONAL COMPUTING RESEARCH
(2022)
Article
Education & Educational Research
Hoang Tieu Binh, Nguyen Quang Trung, Bui The Duy
Summary: This paper introduces a new student responsive model for supporting students using Intelligent Tutoring Systems, proposes a weighted-based model for estimating and suggesting learning materials, conducts empirical research, and demonstrates the effectiveness of the proposed model in ITS.
EDUCATION AND INFORMATION TECHNOLOGIES
(2021)
Article
Green & Sustainable Science & Technology
Angxuan Chen, Huaiya Liu, Kam-Cheong Li, Jiyou Jia
Summary: This paper investigates the effectiveness of developing an Intelligent Tutoring System (ITS) based on Self-Determination Theory (SDT) for student-athletes. The experiment results show a significant improvement in academic engagement and motivation when student-athletes used the SDT-based ITS, while their athletic motivation remained preserved.
Review
Green & Sustainable Science & Technology
Ching-Yi Chang, Hui-Chun Chu
Summary: This study used bibliographic analysis to validate the research trends of technology-enhanced digital storytelling in education and educational research. Through analyzing top journals, frequently cited articles, keywords, research methods, and application domains, the study identified four thematic clusters and highlighted the dominant application domain of activity in DS research. The results provide recommendations for future research.
Article
Education & Educational Research
Aohua Ni, Alan Cheung
Summary: This study examines secondary students' intention and actual use of intelligent tutoring systems (ITS) and proposes an extended technology acceptance model (TAM) to predict their continuance intention. The results show that perceived usefulness and price value directly impact intention, while perceived ease of use indirectly influences intention through perceived usefulness. Learning goal orientation and facilitating conditions positively influence continuance intention through cognitive mediation. Perceived enjoyment positively predicts intention, while anxiety negatively predicts intention.
EDUCATION AND INFORMATION TECHNOLOGIES
(2023)
Article
Psychology, Multidisciplinary
Javier Diez-Palomar, Maria del Socorro Ocampo Castillo, Ariadna Munte Pascual, Esther Oliver
Summary: This study analyzes a case study of an interactive learning environment shared by adults with and without special needs, identifying several improvements in educational outcomes, social inclusion, and well-being for adult learners with SEN.
FRONTIERS IN PSYCHOLOGY
(2021)
Article
Computer Science, Information Systems
Albert Rego, Pedro Luis Gonzalez Ramirez, Jose M. Jimenez, Jaime Lloret
Summary: The study introduces an intelligent system based on reinforcement learning and deep learning for smart home environments to improve user experience. Experimental results show that this system outperforms traditional algorithms and can increase user QoE.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2022)
Review
Computer Science, Interdisciplinary Applications
Galina Deeva, Daria Bogdanova, Estefania Serral, Monique Snoeck, Jochen De Weerdt
Summary: Real-time teacher feedback is crucial for learners' knowledge and skills acquisition. Recent technological advancements have enabled the development of computer tutoring systems that provide personalized feedback, supporting learners in various domains and settings.
COMPUTERS & EDUCATION
(2021)
Article
Computer Science, Information Systems
J. J. Castro-Schez, C. Glez-Morcillo, J. Albusac, D. Vallejo
Summary: The increasing impact of technology is changing the way people learn and institutions teach. Online learning platforms have been created to offer comprehensive and effective educational solutions, but these platforms often restrict students' freedom to experiment with knowledge and propose tasks on their own initiative.
INFORMATION SCIENCES
(2021)
Review
Psychology, Multidisciplinary
Leire Ugalde, Maite Santiago-Garabieta, Beatriz Villarejo-Carballido, Lidia Puigvert
Summary: Inclusive education plays a crucial role in promoting academic learning and cognitive development for children with SEN, and research supports the effectiveness of interactive learning environments in achieving these goals.
FRONTIERS IN PSYCHOLOGY
(2021)
Article
Green & Sustainable Science & Technology
Ninni Singh, Vinit Kumar Gunjan, Amit Kumar Mishra, Ram Krishn Mishra, Nishad Nawaz
Summary: Education is crucial for improving lives and achieving global sustainability. Intelligent systems can assist sustainable education by providing personalized learning environments. This research focuses on imitating human tutor cognitive intelligence to offer quality education. The experimental results demonstrate that the intelligence incorporated SeisTutor enhances learning outcomes compared to systems without intelligence.
Article
Chemistry, Multidisciplinary
Vladimir Bradac, Pavel Smolka, Martin Kotyrba, Tomas Prudek
Summary: The article discusses the construction of an intelligent tutoring system for distance learning and combined forms of studies. The proposed model emphasizes the individual needs of students through an expert system and adaptation mechanisms. The focus on the individuality of students is considered an innovative approach that can be achieved on a large scale.
APPLIED SCIENCES-BASEL
(2022)
Review
Education & Educational Research
Huanhuan Wang, Ahmed Tlili, Ronghuai Huang, Zhenyu Cai, Min Li, Zui Cheng, Dong Yang, Mengti Li, Xixian Zhu, Cheng Fei
Summary: Intelligent Tutoring Systems (ITSs) have the potential to transform teaching and learning, but there are mixed results regarding their effectiveness. This study analyzed 40 qualified studies that used social experiment methods to examine the effectiveness of ITS from 2011 to 2022. The results showed a complex landscape of ITS effectiveness in real educational contexts. There was a need for more research on the impact of ITS on non-cognitive factors, process-oriented factors, and social outcomes. Some studies lacked scientific rigor in experimental design and data analysis. Suggestions for future study and implications were proposed based on the findings.
EDUCATION AND INFORMATION TECHNOLOGIES
(2023)
Article
Computer Science, Interdisciplinary Applications
Tzu-Chi Yang, Meng Chang Chen, Sherry Y. Chen
COMPUTERS & EDUCATION
(2018)
Article
Computer Science, Cybernetics
Tzu-Chi Yang, Meng Chang Chen, Sherry Y. Chen
UNIVERSAL ACCESS IN THE INFORMATION SOCIETY
(2020)
Article
Multidisciplinary Sciences
Yi-Ting Huang, Yeali S. Sun, Meng Chang Chen
Summary: This study develops a sequence-to-sequence neural network called TagSeq to analyze the behavior of malware. By investigating recorded sequences of Windows API calls and generating tags to label malicious behavior, it helps security analysts recognize the actions and intentions of malware.
Article
Computer Science, Artificial Intelligence
Hsin-Chih Yang, Ming-Chuan Yang, Guo-Wei Wong, Meng Chang Chen
Summary: In this study, a self-attention-based neural network is used to predict the anomalies of fine particulate matter (PM2.5), and extreme value theory (EVT) is employed to solve the rarity issue of anomalous data. Experiments show that the proposed model achieves improvements of 478% in F1 score and 286% in Matthews correlation coefficient (MCC) compared to the fully connected network, and 229% in F1 and 148% in MCC compared to the typical transformer trained with the traditional loss function.
IEEE INTELLIGENT SYSTEMS
(2023)
Article
Multidisciplinary Sciences
George William Kibirige, Ming-Chuan Yang, Chao-Lin Liu, Meng Chang Chen
Summary: The paper proposes a new Remote Transported Pollutants (RTP) model that predicts local PM2.5 concentrations more accurately by integrating deep learning components and learning from various domains. Extensive experiments using real-world data demonstrate that the RTP model outperforms other models in predicting pollution events at different time ranges.
Article
Multidisciplinary Sciences
George William Kibirige, Chiao Cheng Huang, Chao Lin Liu, Meng Chang Chen
Summary: PM2.5 prediction is crucial for governments to establish effective policies in controlling atmospheric pollution and protecting public health. We propose a composite neural network model that incorporates aerosol optical depth, weather data, and ocean wind features collected from satellites, overcoming the limitations of traditional machine learning methods. Our findings show that the proposed architecture significantly improves overall performance compared to individual components and ensemble models. The monthly analysis also demonstrates its superiority in regions where land-sea breezes dominate PM2.5 accumulation.
SCIENTIFIC REPORTS
(2023)
Article
Computer Science, Artificial Intelligence
Ming-Chuan Yang, Meng Chang Chen
Summary: This work investigates the framework and statistical performance guarantee of composite neural network for solving complicated applications. It is composed of pre-trained and non-instantiated neural network models, connected in a rooted directed acyclic graph. The advantages of adopting pre-trained models as components are benefiting from domain experts' intelligence and diligence, and saving effort in data acquisition and model training. The study proposes the framework of a composite network and proves its superior performance compared to its pre-trained components in a high probability. Empirical evaluations of the PM2.5 prediction application show that the constructed composite neural network models outperform other machine learning models.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2023)
Article
Computer Science, Hardware & Architecture
Yi-Ting Huang, Chi Yu Lin, Ying-Ren Guo, Kai-Chieh Lo, Yeali S. Sun, Meng Chang Chen
Summary: This research proposes a malicious behavior analysis system based on the MITRE ATT&CK framework, which can effectively detect and respond to cyber threats and provides a mapping from malicious behaviors to ATT&CK techniques and API calls.
IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Faisal Ghaffar, George William Kibirige, Chih-Ya Shen, Meng Chang Chen
2020 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM)
(2020)
Proceedings Paper
Computer Science, Information Systems
Ting-Wei Hsu, Chung-Chi Chen, Hen-Hsen Huang, Meng Chang Chen, Hsin-Hsi Chen
WWW'20: COMPANION PROCEEDINGS OF THE WEB CONFERENCE 2020
(2020)
Article
Computer Science, Theory & Methods
Shun-Wen Hsiao, Yeali S. Sun, Meng Chang Chen
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
(2020)
Proceedings Paper
Computer Science, Information Systems
Yi-Ting Huang, Yu-Yuan Chen, Chih-Chun Yang, Yeali Sun, Shun-Wen Hsiao, Meng Chang Chen
INFORMATION SECURITY AND PRIVACY, ACISP 2019
(2019)
Article
Education & Educational Research
Tzu-Chi Yang, Meng Chang Chen, Sherry Y. Chen
ASIA-PACIFIC EDUCATION RESEARCHER
(2019)
Proceedings Paper
Computer Science, Artificial Intelligence
Ming-Chuan Yang, Meng Chang Chen
2018 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA)
(2018)
Proceedings Paper
Computer Science, Theory & Methods
Shun Chieh Chang, Yeali S. Sun, Wu Long Chuang, Meng Chang Chen, Bo Sun, Takeshi Takahashi
2018 IEEE 23RD PACIFIC RIM INTERNATIONAL SYMPOSIUM ON DEPENDABLE COMPUTING (PRDC)
(2018)
Article
Computer Science, Interdisciplinary Applications
Elise Ameloot, Tijs Rotsaert, Thomas Ameloot, Bart Rienties, Tammy Schellens
Summary: This study investigates the impact of using learning analytics to support students' autonomy and competence needs in a blended learning environment. The findings show that teachers' adaptation based on learning analytics positively influences students' satisfaction with the adapted learning environment. However, students' basic psychological needs vary depending on the face-to-face workshop subject. The study emphasizes the importance of thoughtful blended learning course design and provides recommendations for effective learning analytics utilization in university settings.
COMPUTERS & EDUCATION
(2024)
Article
Computer Science, Interdisciplinary Applications
Tzu-Chi Yang, Zhi-Shen Lin
Summary: Computational thinking is essential in the current era and learning programming is the most effective way to develop it. Introducing computational thinking and programming at an early age is recommended. Graphic organizers serve as a bridge between students' existing knowledge and new learning, enhancing their learning process. The study found that using graphic organizers improved elementary school students' computational thinking, programming skills, and learning experiences.
COMPUTERS & EDUCATION
(2024)
Article
Computer Science, Interdisciplinary Applications
Yuqin Yang, Kaicheng Yuan, Gaoxia Zhu, Lizhen Jiao
Summary: The study finds that the design of collaborative analytics-enhanced reflective assessment can promote conducive epistemic emotions to knowledge building among undergraduates, and enriches our understanding of the relationships between metacognition, epistemic emotions, and knowledge building practices.
COMPUTERS & EDUCATION
(2024)
Article
Computer Science, Interdisciplinary Applications
Vishal Kiran Kuvar, Jeremy N. Bailenson, Caitlin Mills
Summary: Recent research suggests that students' minds often wander off-task during learning, regardless of the learning modality. This study explores the potential of virtual reality (VR) to reduce task-unrelated thoughts (TUT) and finds that learning with VR leads to lower TUT and better performance.
COMPUTERS & EDUCATION
(2024)
Article
Computer Science, Interdisciplinary Applications
Yiming Liu, Jeremy Tzi Dong Ng, Xiao Hu, Zhengyang Ma, Xiaoyan Lai
Summary: This study examines teachers' usage intention and behavior towards the Game Learning Analytics (GLA) system in K-12 classrooms. The study found that personal, environmental, and technological factors influenced teachers' intention and behavior, and that technostress moderated the intention-behavior relationship. The study also identified the heterogeneity of GLA usage among teachers with different individual characteristics.
COMPUTERS & EDUCATION
(2024)
Article
Computer Science, Interdisciplinary Applications
Romina Cachia, Artur Pokropek, Nikoleta Giannoutsou
Summary: This article introduces a shortened version of the European Commission's SELFIE tool for measuring the digital capacity of schools. Two shorter measurement instruments, called midi-SELFIE and mini-SELFIE, are proposed based on the original tool. The validity and uses of these shortened versions are explored through various cases and compared to the complete instrument. The results suggest that the shortened versions of SELFIE are reliable alternatives for specific purposes.
COMPUTERS & EDUCATION
(2024)